Single-Molecule and Cellular Biophysics

For more than a decade the lab has innovated technologies and methods for single-molecule and small-ensemble investigations of biophysical systems at the cellular scale. The group leverages control and systems tools to realize new experimental perspectives and computational methods, distinct from ensemble-average studies that miss the fluctuations and heterogeneity essential to biological function.

Signature contributions include:

• Detection and estimation of events in single-molecule experiments using dynamic programming, with released software used by independent researchers for analyzing DNA and related time-series data.
• A semi-analytical method that significantly reduces the computational burden of rare-event detection in intracellular cargo transport by molecular-motor ensembles, and captures how small teams of motors produce emergent transport properties.
• First mechanical characterization of full-length utrophin, a molecule directly relevant to Duchenne Muscular Dystrophy, in collaboration with the Ervasti lab. Multiple AFM-mode measurements reveal distinct mechanical properties for dystrophin and utrophin not manifest by small fragments.
• Investigation of cargo-motor interaction kinetics and how they regulate myosin-VI-based transport, connecting single-molecule mechanics to cellular function (with the Sivaramakrishnan lab).
• Physics-augmented deep learning for classifying single-molecule force-spectroscopy data — an emerging thread bridging this area with the machine-learning program.
• Quantifying errors in the Jarzynski estimator — connecting statistical-physics estimators for free energies from non-equilibrium measurements to systems-theoretic analysis, feeding back into the foundational work on thermodynamics at the small scale.

The work spans theoretical, computational, learning-based, and experimental efforts, and is supported by NSF, NIH, and the Muscular Dystrophy Association.